Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Author, validate, edit, and render deterministic .zen design docs to PNG/PDF.
Pick the AI app you use, then copy the settings.
Passed 2/2 checks · Runs on your computer
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
Install Node.js on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
One time only; it works for every server that needs Node.js
SettingsDeveloperEdit Config
{
"mcpServers": {
"zenith": {
"command": "npx",
"args": [
"-y",
"@zenitheditor/zenith-mcp"
]
}
}
}Use Zenith and tell me what you can do for me, then show me one thing✓ If Claude says it is using Zenith or shows a Zenith tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect Zenith yet
Zenith runs on your computer, but ChatGPT can only connect servers that run on the web
A · Use an app that can connect Zenith
B · Others in Design, images & audio that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
Works with Claude Code, with some setup first
Install Node.js on your computer first (one time)
One time only; it works for every server that needs Node.js
Mac: press Command+Space and type Terminal · Windows: open PowerShell
claude mcp add --scope user zenith -- npx -y @zenitheditor/zenith-mcpYou should see Zenith listed as connected
Use Zenith and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using Zenith or shows a Zenith tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
Install Node.js on your computer first (one time)
One time only; it works for every server that needs Node.js
Use Zenith and tell me what you can do for me, then show me one thing✓ If Cursor says it is using Zenith or shows a Zenith tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
Install Node.js on your computer first (one time)
One time only; it works for every server that needs Node.js
Use Zenith and tell me what you can do for me, then show me one thing✓ If VS Code says it is using Zenith or shows a Zenith tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Claude Code
claude mcp add --scope user zenith -- npx -y @zenitheditor/zenith-mcpClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"zenith": {
"command": "npx",
"args": [
"-y",
"@zenitheditor/zenith-mcp"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"zenith": {
"command": "npx",
"args": [
"-y",
"@zenitheditor/zenith-mcp"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"zenith": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@zenitheditor/zenith-mcp"
]
}
}
}These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
npm: @zenitheditor/zenith-mcpBased on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 12, 2026
The registry name was verified with the GitHub account zenitheditor, which owns the repo
Code last changed 18 days ago
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Ask, share a tip or report that it does not work. Sorted by what people marked helpful.
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Posts here are written by users, not the PopNx team.
No reviews yet
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 2 of 2 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed 18 days ago, and the latest version (0.0.8) reached the registry 4 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Figma Context MCP, AutoClip, Next AI Draw.io
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Clip long videos into short clips with covers and captions. Local CLI and MCP.
draw.io diagrams your AI agent draws on a live browser canvas that you can also edit by hand
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
A design-document format and engine built for the age of AI agents.
Plain-text .zen design files that you can read, diff, review, validate, and let an agent safely edit — compiled deterministically to pixel-exact PNG, self-contained SVG, and print-ready PDF.
Install Quick start Features Validation Commands Agents
Every banner and diagram in this README is itself created using Zenith — source in assets/showcase/ .
Zenith is a plain-text format and engine for design files — posters, decks, books, social graphics, diagrams, and more. The idea is simple: design should work the way code does. You should be able to read it, diff it, review it, test it, and let an agent safely edit it.
A .zen file is human-readable KDL text. The engine parses it, validates it against a large diagnostic set, compiles it to a backend-neutral scene, and renders the same file to the same pixels every time — as a PNG, self-contained SVG, or print-ready PDF.
The sections below are collapsed to keep this page skimmable — click any heading's ▸ to expand it. Install and Quick start are open by default.
The recommended way to install the zenith CLI is the install script, which detects your platform and downloads the matching prebuilt binary from GitHub Releases.
Linux / macOS
curl -fsSL https://raw.githubusercontent.com/zenitheditor/zenith/main/scripts/install.sh | sh
Windows (PowerShell)
irm https://raw.githubusercontent.com/zenitheditor/zenith/main/scripts/install.ps1 | iex
Set ZENITH_INSTALL_DIR to change the install location (default ~/.local/bin):
ZENITH_INSTALL_DIR=/usr/local/bin \
curl -fsSL https://raw.githubusercontent.com/zenitheditor/zenith/main/scripts/install.sh | sh
cargo install zenith-tool # from crates.io (installs the `zenith` binary)
cargo install --git https://github.com/zenitheditor/zenith zenith-tool # from source
Thirteen library crates are published under their own names for Rust projects that build on the engine directly: zenith-geometry, zenith-session, zenith-core, zenith-layout, zenith-raster, zenith-scene, zenith-perception, zenith-zpx, zenith-render, zenith-tx, zenith-producers, zenith-pipeline, and zenith-editor. zenith-editor-wasm and zenith-editor-bench are not published.
npm install -g @zenitheditor/zenith-mcp
npx -y @zenitheditor/zenith-mcp --help
The npm package installs the matching prebuilt zenith binary from GitHub Releases and is focused on the MCP Registry launch path. The unscoped zenith binary remains the Rust CLI.
Download directly from GitHub Releases:
| Platform | Architecture | Asset |
|---|---|---|
| Linux | x86_64 | zenith- -linux-x64.tar.gz |
| Linux | aarch64 | zenith- -linux-arm64.tar.gz |
| macOS | x86_64 | zenith- -macos-x64.tar.gz |
| macOS | Apple Silicon | zenith- -macos-arm64.tar.gz |
| Windows | x86_64 | zenith- -windows-x64.zip |
zenith update # latest stable release
zenith update --pre # latest prerelease zenith update --version # a specific release tag, e.g. the ones on the Releases page
Verify with zenith --version.
For local development or source installs:
git clone --recurse-submodules https://github.com/zenitheditor/zenith
cd zenith cargo build --release cargo install --path zenith-cli # installs zenith to ~/.cargo/bin ./scripts/install.sh --local # installs the local build to ~/.local/bin
The release binary lands at target/release/zenith. No C toolchain or system libraries are required — the dependency graph is C-free and unsafe is forbidden workspace-wide.
zenith validate examples/hello.zen # report diagnostics (add --json for machine output)
zenith fmt examples/hello.zen # canonical, idempotent formatting zenith fix draft.zen --apply # apply machine fixes (tokens, typos) in one step zenith tokens examples/hello.zen # list design tokens and their resolved values zenith inspect examples/hello.zen # print the node tree (read-only) zenith render examples/hello.zen --png hello.png # render to PNG
zenith render examples/multipage.zen --all-pages out/ # one PNG per page zenith render examples/hello.zen --pdf hello.pdf # print-ready PDF zenith render examples/hello.zen --svg hello.svg # self-contained SVG zenith render examples/multipage.zen --svg page.svg --page 2 zenith render examples/multipage.zen --all-pages-svg svg-pages/ zenith render examples/hello.zen --scene scene.json # dump the scene IR
| Export flag | Output |
|---|---|
--svg OUT | Page 1 by default, with outlined text. |
--pdf OUT | Every page in one PDF by default. |
--page N | Selects one page for single-output flags, including PDF. |
--all-pages-svg DIR | Writes page-N.svg in document order. |
--raster-scale F | SVG/PDF fallback resolution. Finite 0 < F <= 4, default 1. |
--scale F | PNG output scale. Finite 0 < F <= 4, default 1. |
--deny render.svg_rasterized | Blocks SVG exports requiring raster fallback. |
--deny render.pdf_rasterized | Blocks PDF exports requiring raster fallback. |
--raster-scale changes fallback pixels without changing vector geometry or page dimensions. Existing bitmap assets retain source resolution.render.svg_rasterized and render.pdf_rasterized report pages, command ranges, and reasons. JSON includes structured rasterized regions.Vec retain compatibility emission. Use report APIs for strict errors.zenith render examples/multipage.zen --pdf book.pdf --raster-scale 2 --json
zenith render examples/hello.zen --svg hello.svg --raster-scale 2 --json
The smallest valid document:
zenith version=1 {
project id="proj.hello" name="Hello Zenith" tokens format="zenith-token-v1" { token id="color.bg" type="color" value="#f8fafc" token id="color.ink" type="color" value="#111827" token id="font.body" type="fontFamily" value="Noto Sans" token id="size.heading" type="dimension" value=(px)42 } styles {} document id="doc.hello" title="Hello Zenith" { page id="page.hello" w=(px)480 h=(px)160 { rect id="rect.bg" x=(px)0 y=(px)0 w=(px)480 h=(px)160 fill=(token)"color.bg" text id="text.hello" x=(px)24 y=(px)24 w=(px)432 h=(px)112 fill=(token)"color.ink" font-family=(token)"font.body" font-size=(token)"size.heading" { span "Hello Zenith" } } } }
See examples/ for runnable .zen files covering shapes, rich text, inline markdown (loaded from an external file), code blocks, images, frames/groups, multi-page documents and styles, plus the richer features — gradient, shadow, blur, filter, mask, table, flowchart (shapes + connectors), charts (bar/line/area/pie/donut/sparkline, with legends, value labels, and data binding), and anchors.
Code got source control, types, tests, and PRs. Design files got none of that — and that hurts people and blocks AI.
Code got source control, types, tests, and pull requests. Design files got none of that. They're opaque blobs — you can't diff them, you can't review a change, and the same file can render differently on different machines.
That's a problem for people, and it's a bigger problem for AI. Agents can already write code and open pull requests, because code is text they can read and reason about. Drop them into a design tool and they go blind. Ask an agent to "make the heading brand red and tighten the layout" and there's nothing safe to grab onto — no stable target, no validation, no preview, no way to check the result.
Zenith fixes that. The goal is to make design files as safe to automate as code:
The opposite of an image model: Zenith generates the editable design , not a flat picture.
This is the most common mix-up, so it's worth being blunt: Zenith is the opposite of an image model like Nano Banana, ChatGPT image, or Grok Imagine.
An image ge